We propose to continue investigating the dosimetric effects of tissue and applicator heterogeneities in and around brachytherapy implants needed to facilitate integration of accurate prospective dose calculation into clinical brachytherapy. Even though heterogeneities, including metallic applicators, local shielding to spare normal tissue and variations in tissue composition and density, may perturb dose by as much as 50%, these effects are almost universally ignored by conventional treatment planning. Historically, brachytherapy has evolved through empirical observation of clinical outcome rather than by optimization of treatment technique to satisfy desired dosimetric constraints. However several promising developments, including image-based 3D treatment planning, high dose-rate brachytherapy and new low-energy sources for brachytherapy, aim to improve the balance between local control and complications through optimization of the dose distribution. Realization of this potential requires extensive empirical characterization of tissue heterogeneity and applicator effects as well as tools for accurate prediction of these effects both for applicator design and for planning individual treatments. Currently, both the phenomenology of heterogeneity effects and limitations of dose-measurement instrumentation, radiation-transport calculations, and dose-computation algorithms in characterizing these effects are poorly understood. Our program consists of four inter-related and dynamically interacting specific aims. First, an extensive program of dose measurement around heterogeneities near I-125, Yb-169, Ir-192 and Cs-137 is proposed. The aim is to validate Monte Carlo simulation as a reliable and accurate clinical dosimetry tool for predicting dose in heterogeneous geometries, designing applicators and sources to exploit these effects, and for characterizing the response and limitations of dose detectors. Secondly, Monte Carlo simulation will be used to conduct systematic parametric studies to uncover the dependence of dose-perturbation factors on composition, density, size, shape and location of heterogeneities. These results will direct design of experiments to most conclusively test Monte Carlo simulation. These studies will also define the range of phenomena and levels of complexity and accuracy that dose-computation algorithms must to support in order to predict dose with 5-7% accuracy in clinically-relevant settings. Thirdly, we propose to utilize dual-energy CT-scanning to define the composition and geometric architecture of soft tissue, bone and air-cavity heterogeneities in and around common human implant sites. This study will identify the clinically relevant aspects of these potentially complex dosimetric effects and will effectively target our proposed algorithm-development, parametric studies and dose-measurement programs. Finally, we propose to continue our highly promising work in development of heterogeneity correction algorithms for clinical treatment planning. Design endpoints include clinically-realistic levels of accuracy, execution speed and domain of applicability.